DATA MINING TECHNIQUES AS A TOOL IN NEUROLOGICAL DISORDERS DIAGNOSIS

被引:5
|
作者
Zdrodowska, Malgorzata [1 ]
Dardzinska, Agnieszka [1 ]
Chorazy, Monika [2 ]
Kulakowska, Alina [2 ]
机构
[1] Bialystok Tech Univ, Dept Biocybernet & Biomed Engn, Fac Mech Engn, Ul Wiejska 45C, PL-15351 Bialystok, Poland
[2] Med Univ Bialystok, Dept Neurol, Fac Med, Ul M Sklodowskiej Curie 24A, PL-15276 Bialystok, Poland
关键词
Data Mining; Classification Rules; Decision Tree; Action Rules; Neurological Disorders; Stroke; Multiple Sclerosis;
D O I
10.2478/ama-2018-0033
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Neurological disorders are diseases of the brain, spine and the nerves that connect them. There are more than 600 diseases of the nervous system, such as epilepsy, Parkinson's disease, brain tumors, and stroke as well as less familiar ones such as multiple sclerosis or frontotemporal dementia. The increasing capabilities of neurotechnologies are generating massive volumes of complex data at a rapid pace. Evaluating and diagnosing disorders of the nervous system is a complicated and complex task. Many of the same or similar symptoms happen in different combinations among the different disorders. This paper provides a survey of developed selected data mining methods in the area of neurological diseases diagnosis. This review will help experts to gain an understanding of how data mining techniques can assist them in neurological diseases diagnosis and patients treatment.
引用
收藏
页码:217 / 220
页数:4
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